Instructions to use sdasdasdas11/anggimozzi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use sdasdasdas11/anggimozzi with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="sdasdasdas11/anggimozzi", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Agenlus Model Hub π
Welcome to your Agenlus Reinforcement Learning repository! This repository hosts multiple trained models.
π Models Summary
| Model Name | Environment | Algorithm | Best Score | Episodes | Links |
|---|---|---|---|---|---|
| DQN-CartPole-v1-ep3 | CartPole-v1 |
DQN |
17.67 | 3 | Browse Files |
π Model Details & Instructions
π¦ DQN-CartPole-v1-ep3
- Environment:
CartPole-v1 - RL Algorithm:
DQN - Best Avg Reward:
17.67 - Episodes Trained:
3
Description: DQN model trained on CartPole-v1 for 3 episodes. Best avg reward: 17.67.
How to load:
const model = await tf.loadLayersModel('https://huggingface.co/sdasdasdas11/anggimozzi/raw/main/DQN-CartPole-v1-ep3/model.json');
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